@inproceedings {INPROC-2016-54, author = {Henri Tokola and Christoph Gr{\"o}ger and Eeva J{\"a}rvenp{\"a}{\"a} and Esko Niemi}, title = {{Designing Manufacturing Dashboards on the Basis of a Key Performance Indicator Survey}}, booktitle = {Proceedings of the 49th CIRP Conference on Manufacturing Systems (CIRP CMS)}, publisher = {Elsevier}, institution = {University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Germany}, series = {Procedia CIRP}, volume = {57}, pages = {619--624}, type = {Conference Paper}, month = {May}, year = {2016}, keywords = {Dashboards; Key Performance Indicators (KPIs); Scorecard}, language = {English}, cr-category = {J.1 Administration Data Processing}, department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems}, abstract = {Target-oriented and real-time information provisioning across all hierarchy levels, from shop floor to top floor, is an important success factory for manufacturing companies to facilitate agile and efficient manufacturing. In general, dashboards – in terms of digital single-screen displays – address this challenge and support intuitive monitoring and visualisation of business performance information. Yet, existing dashboard research mainly focus on IT issues and lack a systematic study of the dashboard content. To address this gap, in this paper, we design three representative dashboards for manufacturing companies based on a comprehensive survey that focuses on suitable key performance indicators for different manufacturing target groups. The paper consists of three parts. First, the paper provides a literature review about design principles of dashboards. Second, it publishes the results of a survey of manufacturing companies on preferred key performance indicators (KPIs) for dashboards and the use of dashboards. Third, using the results obtained from the survey, three representative manufacturing dashboards are designed: an operational dashboard for workers, a tactical dashboard for managers and a strategy dashboard for executives. The results underline that different KPIs are preferred for dashboards on different hierarchy levels and that mobile usage of dashboards, especially on tablet pcs, is favoured.}, url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2016-54&engl=1} } @inproceedings {INPROC-2016-42, author = {Frank Steimle and Matthias Wieland}, title = {{ECHO – An mHealth Solution to Support Treatment of Chronic Patients}}, booktitle = {Proceedings of the 8th Central European Workshop on Services and their Composition, ZEUS 2016}, editor = {Christoph Hochreiner and Stefan Schulte}, publisher = {CEUR Workshop Proceedings}, institution = {University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Germany}, pages = {64--67}, type = {Demonstration}, month = {February}, year = {2016}, keywords = {mHealth; eHealth; Monitoring; Cloud Computing; Analysis}, language = {German}, cr-category = {C.2.4 Distributed Systems, H.2.8 Database Applications, J.3 Life and Medical Sciences}, ee = {http://ceur-ws.org/Vol-1562/}, department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems}, abstract = {More and more people all over the world suffer from chronic diseases, like asthma. The German-Greek bilateral research project Enhancing Chronic Patients Health Online developed online services for physicians and patients for use on smart phones or web browsers, in order to improve monitoring of those patients and to be able to detect possible exacerbations earlier. During the project we have developed smart phone applications and websites for both patients and physicians and a cloud-based health data management system. This demonstration shows how our system supports physicians and patients.}, url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2016-42&engl=1} } @inproceedings {INPROC-2016-39, author = {Ana Cristina Franco da Silva and Uwe Breitenb{\"u}cher and K{\'a}lm{\'a}n K{\'e}pes and Oliver Kopp and Frank Leymann}, title = {{OpenTOSCA for IoT: Automating the Deployment of IoT Applications based on the Mosquitto Message Broker}}, booktitle = {Proceedings of the 6th International Conference on the Internet of Things (IoT)}, address = {Stuttgart}, publisher = {ACM}, institution = {University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Germany}, pages = {181--182}, type = {Demonstration}, month = {November}, year = {2016}, isbn = {978-1-4503-4814-0/16/11}, doi = {10.1145/2991561.2998464}, keywords = {Internet of Things; Cyber-Physical Systems; Sensor Integration; Message Broker; Mosquitto; MQTT; TOSCA}, language = {English}, cr-category = {K.6 Management of Computing and Information Systems, D.2.12 Software Engineering Interoperability}, contact = {For questions, feel free to contact me franco-da-silva@ipvs.uni-stuttgart.de}, department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems; University of Stuttgart, Institute of Architecture of Application Systems}, abstract = {Automating the deployment of IoT applications is a complex challenge, especially if multiple heterogeneous sensors, actuators, and business components have to be integrated. This demonstration paper presents a generic, standards-based system that is able to fully automatically deploy IoT applications based on the TOSCA standard, the standardized MQTT messaging protocol, the Mosquitto message broker, and the runtime environment OpenTOSCA. We describe a demonstration scenario and explain in detail how this scenario can be deployed fully automatically using the mentioned technologies.}, url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2016-39&engl=1} } @inproceedings {INPROC-2016-35, author = {Jan K{\"o}nigsberger and Bernhard Mitschang}, title = {{A Semantically-enabled SOA Governance Repository}}, booktitle = {Proceedings of the 2016 IEEE 17th International Conference on Information Reuse and Integration}, editor = {IEEE Computer Society}, address = {Los Alamitos, California, Washington, Tokyo}, publisher = {IEEE Computer Society Conference Publishing Services}, institution = {University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Germany}, pages = {423--432}, type = {Conference Paper}, month = {August}, year = {2016}, isbn = {978-1-5090-3207-5}, keywords = {SOA; Governance; Repository; Semantic Web}, language = {English}, cr-category = {D.2.11 Software Engineering Software Architectures, H.3.5 Online Information Services, I.2.4 Knowledge Representation Formalisms and Methods}, department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems}, abstract = {Companies in today's world need to cope with an ever greater need for flexible and agile IT systems to keep up with the competition and rapidly changing markets. This leads to increasingly complex system landscapes that are often realized using service-oriented architectures (SOA). Companies often struggle to handle the complexity and the governance activities necessary after this paradigm shift. We therefore present a semantically-enabled SOA Governance Repository as the central tool to manage and govern all SOA-related activities within a company. This repository is based on our previously defined key governance aspects as well as our SOA Governance Meta Model (SOA-GovMM). We describe how our repository is able to support and improve the speed and flexibility of company's IT processes.}, url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2016-35&engl=1} } @inproceedings {INPROC-2016-30, author = {Pascal Hirmer}, title = {{Flexible Execution and Modeling of Data Processing and Integration Flows}}, booktitle = {Proceedings of the 10th Advanced Summer School on Service Oriented Computing}, editor = {Johanna Barzen and Rania Khalaf and Frank Leymann and Bernhard Mitschang}, publisher = {IBM Research Report}, institution = {University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Germany}, pages = {26--40}, type = {Conference Paper}, month = {September}, year = {2016}, keywords = {Big Data; Data Integration; Data Flows; Pipes and Filters}, language = {English}, cr-category = {E.0 Data General, E.1 Data Structures, H.1 Models and Principles}, ee = {http://domino.research.ibm.com/library/cyberdig.nsf/papers/EC7D5D883519DC7E85258035004DBD19/$File/rc25624.pdf}, contact = {Pascal.Hirmer@ipvs.uni-stuttgart.de}, department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems}, abstract = {Today, the amount of data highly increases within all domains due to cheap hardware, fast network connections, and an increasing digitization. Deriving information and, as a consequence, knowledge from this huge amount of data is a complex task. Data sources are oftentimes very heterogeneous, dynamic, and distributed. This makes it difficult to extract, transform, process and integrate data, which is necessary to gain this knowledge. Furthermore, extracting knowledge oftentimes requires technical experts with the necessary skills to conduct the required techniques. For my PhD thesis, I am working on a new and improved approach for data extraction, processing, and integration by: (i) facilitating the definition and processing of data processing and integration scenarios through graphical creation of flow models, (ii) enabling an ad-hoc, iterative and explorative approach to receive high-quality results, and (iii) a flexible execution of the data processing tailor-made for users’ non-functional requirements. By providing these means, I enable a more flexible data processing by a wider range of users, not only limited to technical experts. This paper describes the approach of the thesis as well as the publications until today.}, url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2016-30&engl=1} } @inproceedings {INPROC-2016-29, author = {Cornelia Kiefer}, title = {{Assessing the Quality of Unstructured Data: An Initial Overview}}, booktitle = {Proceedings of the LWDA 2016 Proceedings (LWDA)}, editor = {Ralf Krestel and Davide Mottin and Emmanuel M{\"u}ller}, address = {Aachen}, publisher = {CEUR Workshop Proceedings}, institution = {University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Germany}, pages = {62--73}, type = {Conference Paper}, month = {September}, year = {2016}, isbn = {1613-0073}, keywords = {quality of unstructured data, quality of text data, data, quality dimensions, data quality assessment, data quality metrics}, language = {English}, cr-category = {A.1 General Literature, Introductory and Survey, I.2.7 Natural Language Processing}, ee = {http://ceur-ws.org/Vol-1670/paper-25.pdf, http://ceur-ws.org/Vol-1670/}, contact = {cornelia.kiefer@gsame.uni-stuttgart.de}, department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems}, abstract = {In contrast to structured data, unstructured data such as texts, speech, videos and pictures do not come with a data model that enables a computer to use them directly. Nowadays, computers can interpret the knowledge encoded in unstructured data using methods from text analytics, image recognition and speech recognition. Therefore, unstructured data are used increasingly in decision-making processes. But although decisions are commonly based on unstructured data, data quality assessment methods for unstructured data are lacking. We consider data analysis pipelines built upon two types of data consumers, human consumers that usually come at the end of the pipeline and non-human / machine consumers (e.g., natural language processing modules such as part of speech tagger and named entity recognizer) that mainly work intermediate. We define data quality of unstructured data via (1) the similarity of the input data to the data expected by these consumers of unstructured data and via (2) the similarity of the input data to the data representing the real world. We deduce data quality dimensions from the elements in analytic pipelines for unstructured data and characterize them. Finally, we propose automatically measurable indicators for assessing the quality of unstructured text data and give hints towards an implementation.}, url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2016-29&engl=1} } @inproceedings {INPROC-2016-28, author = {C. Timurhan Sungur and Uwe Breitenb{\"u}cher and Oliver Kopp and Frank Leymann and Mozi Song and Andreas Wei{\ss} and Christoph Mayr-Dorn and Schahram Dustdar}, title = {{Identifying Relevant Resources and Relevant Capabilities of Collaborations - A Case Study}}, booktitle = {Proceedings of the 2016 IEEE 20th International Enterprise Distributed Object Computing Workshop (EDOCW)}, publisher = {IEEE Computer Society}, institution = {University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Germany}, pages = {352--355}, type = {Demonstration}, month = {September}, year = {2016}, keywords = {Organizational performance; resource discovery; capability discovery; relevant resources; relevant capabilities; informal processes; unstructured processes}, language = {English}, cr-category = {H.4.1 Office Automation, H.3.3 Information Search and Retrieval, H.3.4 Information Storage and Retrieval Systems and Software, H.5.3 Group and Organization Interfaces}, department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems; University of Stuttgart, Institute of Architecture of Application Systems}, abstract = {Organizational processes involving collaborating resources, such as development processes, innovation processes, and decision-making processes, typically affect the performance of many organizations. Moreover, including required but missing, resources and capabilities of collaborations can improve the performance of corresponding processes drastically. In this work, we demonstrate the extended Informal Process Execution (InProXec) method for identifying resources and capabilities of collaborations using a case study on the Apache jclouds project.}, url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2016-28&engl=1} } @inproceedings {INPROC-2016-25, author = {Pascal Hirmer and Matthias Wieland and Uwe Breitenb{\"u}cher and Bernhard Mitschang}, title = {{Dynamic Ontology-based Sensor Binding}}, booktitle = {Advances in Databases and Information Systems. 20th East European Conference, ADBIS 2016, Prague, Czech Republic, August 28-31, 2016, Proceedings}, address = {Prague, Czech Republic}, publisher = {Springer International Publishing}, institution = {University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Germany}, series = {Information Systems and Applications, incl. Internet/Web, and HCI}, volume = {9809}, pages = {323--337}, type = {Conference Paper}, month = {August}, year = {2016}, isbn = {978-3-319-44039-2}, isbn = {978-3-319-44038-5}, doi = {10.1007/978-3-319-44039-2}, keywords = {Internet of Things; Sensors; Ontologies; Data Provisioning}, language = {English}, cr-category = {E.0 Data General, B.8 Performance and Reliability}, ee = {http://www.springer.com/de/book/9783319440385}, contact = {pascal.hirmer@ipvs.uni-stuttgart.de}, department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems; University of Stuttgart, Institute of Architecture of Application Systems}, abstract = {In recent years, the Internet of Things gains more and more attention through cheap hardware devices and, consequently, an increased interconnection of them. These devices equipped with sensors and actuators form the foundation for so called smart environments that enable monitoring as well as self-organization. However, an efficient sensor registration, binding, and sensor data provisioning is still a major issue for the Internet of Things. Usually, these steps can take up to days or even weeks due to a manual configuration and binding by sensor experts that furthermore have to communicate with domain-experts that define the requirements, e.g. the types of sensors, for the smart environments. In previous work, we introduced a first vision of a method for automated sensor registration, binding, and sensor data provisioning. In this paper, we further detail and extend this vision, e.g., by introducing optimization steps to enhance efficiency as well as effectiveness. Furthermore, the approach is evaluated through a prototypical implementation.}, url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2016-25&engl=1} } @inproceedings {INPROC-2016-24, author = {Alexander Bergmayr and Uwe Breitenb{\"u}cher and Oliver Kopp and Manuel Wimmer and Gerti Kappel and Frank Leymann}, title = {{From Architecture Modeling to Application Provisioning for the Cloud by Combining UML and TOSCA}}, booktitle = {Proceedings of the 6th International Conference on Cloud Computing and Services Science (CLOSER 2016)}, publisher = {SCITEPRESS}, institution = {University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Germany}, pages = {97--108}, type = {Conference Paper}, month = {April}, year = {2016}, doi = {10.5220/0005806900970108}, isbn = {978-989-758-182-3}, keywords = {TOSCA; UML; Model-Driven Software Engineering; Cloud Computing; Cloud Modeling}, language = {English}, cr-category = {K.6 Management of Computing and Information Systems}, department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems; University of Stuttgart, Institute of Architecture of Application Systems}, abstract = {Recent efforts to standardize a deployment modeling language for cloud applications resulted in TOSCA. At the same time, the software modeling standard UML supports architecture modeling from different viewpoints. Combining these standards from cloud computing and software engineering would allow engineers to refine UML architectural models into TOSCA deployment models that enable automatic provisioning of cloud applications. However, this refinement task is currently carried out manually by recreating TOSCA models from UML models because a conceptual mapping between the two languages as basis for an automated translation is missing. In this paper, we exploit cloud modeling extensions to UML called CAML as the basis for our approach CAML2TOSCA, which aims at bridging UML and TOSCA. The validation of our approach shows that UML models can directly be injected into a TOSCA-based provisioning process. As current UML modeling tools lack cloud-based refinement support for deployment models, the added value of CAML2TOSCA is emphasized because it provides the glue between architecture modeling and application provisioning.}, url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2016-24&engl=1} } @inproceedings {INPROC-2016-22, author = {Pascal Hirmer and Matthias Wieland and Uwe Breitenb{\"u}cher and Bernhard Mitschang}, title = {{Automated Sensor Registration, Binding and Sensor Data Provisioning}}, booktitle = {Proceedings of the CAiSE'16 Forum, at the 28th International Conference on Advanced Information Systems Engineering (CAiSE 2016)}, address = {Ljubljana, Slovenia}, publisher = {CEUR-WS.org}, institution = {University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Germany}, series = {CEUR Workshop Proceedings}, volume = {1612}, pages = {81--88}, type = {Conference Paper}, month = {June}, year = {2016}, issn = {1613-0073}, keywords = {Internet of Things; Sensors; Ontologies; Data Provisioning}, language = {English}, cr-category = {J.6 Computer-Aided Engineering, H.3.1 Content Analysis and Indexing}, ee = {http://ceur-ws.org/Vol-1612/paper11.pdf}, contact = {pascal.hirmer@ipvs.uni-stuttgart.de}, department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems}, abstract = {Today, the Internet of Things has evolved due to an increasing interconnection of technical devices. However, the automated binding and management of things and sensors is still a major issue. In this paper, we present a method and system architecture for sensor registration, binding, and sensor data provisioning. This approach enables automated sensor integration and data processing by accessing the sensors and provisioning the data. Furthermore, the registration of new sensors is done in an automated way to avoid a complex, tedious manual registration. We enable (i) semantic description of sensors and things as well as their attributes using ontologies, (ii) the registration of sensors of a physical thing, (iii) a provisioning of sensor data using different data access paradigms, and (iv) dynamic sensor binding based on application requirements. We provide the Resource Management Platform as a prototypical implementation of the architecture and corresponding runtime measurements}, url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2016-22&engl=1} } @inproceedings {INPROC-2016-21, author = {C. Timurhan Sungur and Uwe Breitenb{\"u}cher and Frank Leymann and Matthias Wieland}, title = {{Context-sensitive Adaptive Production Processes}}, booktitle = {Proceedings of the 48th CIRP Conference on Manufacturing Systems}, publisher = {Elsevier}, institution = {University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Germany}, series = {Procedia CIRP}, volume = {41}, pages = {147--152}, type = {Conference Paper}, month = {February}, year = {2016}, doi = {10.1016/j.procir.2015.12.076}, keywords = {Process; Automation; Optimization; Adaptation}, language = {English}, cr-category = {H.4.1 Office Automation, H.5.3 Group and Organization Interfaces}, department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems; University of Stuttgart, Institute of Architecture of Application Systems}, abstract = {To stay competitive, manufacturing companies need to adapt their processes in a regular basis to the most recent conditions in their corresponding domains. These adaptations are typically the result of turbulences, such as changes in human resources, new technological advancements, or economic crises. Therefore, to increase the efficiency of production processes, (i) automation, (ii) optimization, and (iii) dynamic adaptation became the most important requirements in this field. In this work, we propose a novel process modelling and execution approach for creating self-organizing processes: Production processes are extended by context-sensitive execution steps, for which sub-processes are selected, elected, optimized, and finally executed on runtime. During the election step, the most desired solution is chosen and optimized based on selection and optimization strategies of the respective processes. Moreover, we present a system architecture for modelling and executing these context-sensitive production processes.}, url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2016-21&engl=1} } @inproceedings {INPROC-2016-10, author = {Christoph Stach}, title = {{Secure Candy Castle - A Prototype for Privacy-Aware mHealth Apps}}, booktitle = {Proceedings of the 17th International Conference on Mobile Data Management}, address = {Porto}, publisher = {IEEE Computer Society Conference Publishing Services}, institution = {University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Germany}, pages = {361--364}, type = {Demonstration}, month = {June}, year = {2016}, keywords = {mHealth; privacy; diagnostic game; diabetes}, language = {English}, cr-category = {K.4.1 Computers and Society Public Policy Issues, D.4.6 Operating Systems Security and Protection, K.8 Personal Computing, J.3 Life and Medical Sciences}, contact = {Senden Sie eine E-Mail an Christoph.Stach@ipvs.uni-stuttgart.de}, department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems}, abstract = {Due to rising medical costs, the healthcare landscape is on the move. Novel treatment methods are badly required. Especially for the treatment of chronic diseases the usage of smart devices in combination with medical devices for telemedical screenings is a promising approach. If the patients are not in control of the collection and processing of their health data, privacy concerns limit their willingness to use such a method. In this paper, we present a prototype for an Android-based privacy-aware health game for children suffering from diabetes called Secure Candy Castle. In the game, the player keeps an electronic diabetes diary in a playful manner. In doing this, s/he is supported by various sensors. His or her data is analyzed and in case of a critical health condition, the game notifies authorized persons. With our approach, the user stays in control over his or her data, i.e., s/he defines which data should be shared with the game, how accurate this data should be, and even how the data is processed by the game. For this purpose, we apply the Privacy Management Platform, a fine-grained and extendable permission system.}, url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2016-10&engl=1} } @inproceedings {INPROC-2016-09, author = {Christoph Stach and Bernhard Mitschang}, title = {{The Secure Data Container: An Approach to Harmonize Data Sharing with Information Security}}, booktitle = {Proceedings of the 17th International Conference on Mobile Data Management}, address = {Porto}, publisher = {IEEE Computer Society Conference Publishing Services}, institution = {University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Germany}, pages = {292--297}, type = {Conference Paper}, month = {June}, year = {2016}, keywords = {smart devices; information security; data sharing}, language = {English}, cr-category = {K.4.1 Computers and Society Public Policy Issues, D.4.6 Operating Systems Security and Protection}, contact = {Senden Sie eine E-Mail an Christoph.Stach@ipvs.uni-stuttgart.de}, department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems}, abstract = {Smart devices became Marc Weiser's Computer of the 21st Century. Due to their versatility a lot of private data enriched by context data are stored on them. Even the health industry utilizes smart devices as portable health monitors and enablers for telediagnosis. So they represent a severe risk for information security. Yet the platform providers' countermeasures to these threats are by no means sufficient. In this paper we describe how information security can be improved. Therefore, we postulate requirements towards a secure handling of data. Based on this requirements specification, we introduce a secure data container as an extension for the Privacy Management Platform. Since a complete isolation of an app is usually not practicable, our approach also provides secure data sharing features. Finally, we evaluate our approach from a technical point of view as well as a security point of view and show its applicability in an eHealth scenario.}, url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2016-09&engl=1} } @inproceedings {INPROC-2016-07, author = {Christoph Gr{\"o}ger and Laura Kassner and Eva Hoos and Jan K{\"o}nigsberger and Cornelia Kiefer and Stefan Silcher and Bernhard Mitschang}, title = {{The Data-Driven Factory. Leveraging Big Industrial Data for Agile, Learning and Human-Centric Manufacturing}}, booktitle = {Proceedings of the 18th International Conference on Enterprise Information Systems}, editor = {Slimane Hammoudi and Leszek Maciaszek and Michele M. Missikoff and Olivier Camp and Jose Cordeiro}, publisher = {SciTePress}, institution = {University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Germany}, pages = {40--52}, type = {Conference Paper}, month = {April}, year = {2016}, isbn = {978-989-758-187-8}, keywords = {IT Architecture, Data Analytics, Big Data, Smart Manufacturing, Industrie 4.0}, language = {English}, cr-category = {H.4.0 Information Systems Applications General, J.2 Physical Sciences and Engineering}, contact = {Email an Christoph.Groeger@ipvs.uni-stuttgart.de oder laura.kassner@ipvs.uni-stuttgart.de}, department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems}, abstract = {Global competition in the manufacturing industry is characterized by ever shorter product life cycles, increas-ing complexity and a turbulent environment. High product quality, continuously improved processes as well as changeable organizational structures constitute central success factors for manufacturing companies. With the rise of the internet of things and Industrie 4.0, the increasing use of cyber-physical systems as well as the digitalization of manufacturing operations lead to massive amounts of heterogeneous industrial data across the product life cycle. In order to leverage these big industrial data for competitive advantages, we present the concept of the data-driven factory. The data-driven factory enables agile, learning and human-centric manu-facturing and makes use of a novel IT architecture, the Stuttgart IT Architecture for Manufacturing (SITAM), overcoming the insufficiencies of the traditional information pyramid of manufacturing. We introduce the SITAM architecture and discuss its conceptual components with respect to service-oriented integration, ad-vanced analytics and mobile information provisioning in manufacturing. Moreover, for evaluation purposes, we present a prototypical implementation of the SITAM architecture as well as a real-world application sce-nario from the automotive industry to demonstrate the benefits of the data-driven factory.}, url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2016-07&engl=1} } @inproceedings {INPROC-2016-06, author = {Laura Kassner and Bernhard Mitschang}, title = {{Exploring Text Classification for Messy Data: An Industry Use Case for Domain-Specific Analytics}}, booktitle = {Advances in Database Technology - EDBT 2016, 19th International Conference on Extending Database Technology, Bordeaux, France, March 15-16, Proceedings}, publisher = {OpenProceedings.org}, institution = {University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Germany}, pages = {491--502}, type = {Conference Paper}, month = {March}, year = {2016}, isbn = {978-3-89318-070-7}, keywords = {recommendation system; automotive; text analytics; domain-specific language; automatic classification}, language = {English}, cr-category = {H.3.1 Content Analysis and Indexing, H.3.3 Information Search and Retrieval, H.4.2 Information Systems Applications Types of Systems, J.1 Administration Data Processing}, ee = {http://openproceedings.org/2016/conf/edbt/paper-52.pdf}, contact = {Email an laura.kassner@ipvs.uni-stuttgart.de}, department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems}, abstract = {Industrial enterprise data present classification problems which are different from those problems typically discussed in the scientific community -- with larger amounts of classes and with domain-specific, often unstructured data. We address one such problem through an analytics environment which makes use of domain-specific knowledge. Companies are beginning to use analytics on large amounts of text data which they have access to, but in day-to-day business, manual effort is still the dominant method for processing unstructured data. In the face of ever larger amounts of data, faster innovation cycles and higher product customization, human experts need to be supported in their work through data analytics. In cooperation with a large automotive manufacturer, we have developed a use case in the area of quality management for supporting human labor through text analytics: When processing damaged car parts for quality improvement and warranty handling, quality experts have to read text reports and assign error codes to damaged parts. We design and implement a system to recommend likely error codes based on the automatic recognition of error mentions in textual quality reports. In our prototypical implementation, we test several methods for filtering out accurate recommendations for error codes and develop further directions for applying this method to a competitive business intelligence use case.}, url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2016-06&engl=1} } @article {ART-2016-26, author = {Uwe Breitenb{\"u}cher and Christian Endres and K{\'a}lm{\'a}n K{\'e}pes and Oliver Kopp and Frank Leymann and Sebastian Wagner and Johannes Wettinger and Michael Zimmermann}, title = {{The OpenTOSCA Ecosystem - Concepts \& Tools}}, journal = {European Space project on Smart Systems, Big Data, Future Internet - Towards Serving the Grand Societal Challenges - Volume 1: EPS Rome 2016}, publisher = {SciTePress}, pages = {112--130}, type = {Article in Journal}, month = {December}, year = {2016}, isbn = {978-989-758-207-3}, doi = {10.5220/0007903201120130}, keywords = {TOSCA; OpenTOSCA; Orchestration; Management; Cloud}, language = {English}, cr-category = {D.2.2 Software Engineering Design Tools and Techniques, D.2.9 Software Engineering Management}, department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems; University of Stuttgart, Institute of Architecture of Application Systems}, abstract = {Automating the provisioning and management of Cloud applications is one of the most important issues in Cloud Computing. The Topology and Orchestration Specification for Cloud Applications (TOSCA) is an OASIS standard for describing Cloud applications and their management in a portable and interoperable manner. TOSCA enables modeling the application's structure in the form of topology models and employs the concept of executable management plans to describe all required management functionality regarding the application. In this paper, we give an overview of TOSCA and the OpenTOSCA Ecosystem, which is an implementation of the TOSCA standard. The ecosystem consists of standard-compliant tools that enable modeling application topology models and automating the provisioning and management of the modeled applications.}, url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=ART-2016-26&engl=1} } @article {ART-2016-23, author = {Pascal Hirmer and Uwe Breitenb{\"u}cher and Ana Cristina Franco da Silva and K{\'a}lm{\'a}n K{\'e}pes and Bernhard Mitschang and Matthias Wieland}, title = {{Automating the Provisioning and Configuration of Devices in the Internet of Things}}, journal = {Complex Systems Informatics and Modeling Quarterly}, publisher = {Online}, volume = {9}, pages = {28--43}, type = {Article in Journal}, month = {December}, year = {2016}, doi = {10.7250/csimq.2016-9.02}, issn = {2255 - 9922}, keywords = {Internet of Things; sensors; actuators; digital twin; ontologies; TOSCA}, language = {English}, cr-category = {J.6 Computer-Aided Engineering, H.3.1 Content Analysis and Indexing}, ee = {https://csimq-journals.rtu.lv/article/view/csimq.2016-9.02/pdf_8}, contact = {pascal.hirmer@ipvs.uni-stuttgart.de}, department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems}, abstract = {The Internet of Things benefits from an increasing number of interconnected technical devices. This has led to the existence of so-called smart environments, which encompass one or more devices sensing, acting, and automatically performing different tasks to enable their self-organization. Smart environments are divided into two parts: the physical environment and its digital representation, oftentimes referred to as digital twin. However, the automated binding and monitoring of devices of smart environments are still major issues. In this article we present a method and system architecture to cope with these challenges by enabling (i) easy modeling of sensors, actuators, devices, and their attributes, (ii) dynamic device binding based on their type, (iii) the access to devices using different paradigms, and (iv) the monitoring of smart environments in regard to failures or changes. We furthermore provide a prototypical implementation of the introduced approach.}, url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=ART-2016-23&engl=1} } @article {ART-2016-19, author = {Marina Bitsaki and Christos Koutras and George Koutras and Frank Leymann and Frank Steimle and Sebastian Wagner and Matthias Wieland}, title = {{ChronicOnline: Implementing a mHealth solution for monitoring and early alerting in chronic obstructive pulmonary disease}}, journal = {Health Informatics Journal}, publisher = {Sage Publications}, pages = {1--10}, type = {Article in Journal}, month = {April}, year = {2016}, doi = {10.1177/1460458216641480}, keywords = {chronic obstructive pulmonary disease; cloud computing; health services; mobile applications; monitoring}, language = {English}, cr-category = {C.2.4 Distributed Systems, H.2.8 Database Applications, J.3 Life and Medical Sciences}, ee = {http://jhi.sagepub.com/content/early/2016/04/16/1460458216641480.full.pdf+html}, department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems; University of Stuttgart, Institute of Architecture of Application Systems}, abstract = {Lack of time or economic difficulties prevent chronic obstructive pulmonary disease patients from communicating regularly with their physicians, thus inducing exacerbation of their chronic condition and possible hospitalization. Enhancing Chronic patients{\^a}€™ Health Online proposes a new, sustainable and innovative business model that provides at low cost and at significant savings to the national health system, a preventive health service for chronic obstructive pulmonary disease patients, by combining human medical expertise with state-of-the-art online service delivery based on cloud computing, service-oriented architecture, data analytics, and mobile applications. In this article, we implement the frontend applications of the Enhancing Chronic patients{\^a}€™ Health Online system and describe their functionality and the interfaces available to the users.}, url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=ART-2016-19&engl=1} } @article {ART-2016-18, author = {Frank Steimle and Matthias Wieland and Bernhard Mitschang and Sebastian Wagner and Frank Leymann}, title = {{Extended provisioning, security and analysis techniques for the ECHO health data management system}}, journal = {Computing}, publisher = {Springer}, pages = {1--19}, type = {Article in Journal}, month = {October}, year = {2016}, doi = {10.1007/s00607-016-0523-8}, language = {English}, cr-category = {C.2.4 Distributed Systems, H.2.8 Database Applications, J.3 Life and Medical Sciences}, ee = {http://dx.doi.org/10.1007/s00607-016-0523-8}, department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems}, abstract = {eHealth gains more and more interest since a lot of end-user devices supporting health data capturing are available. The captured data has to be managed and securely stored, in order to access it from different devices and share it with other users such as physicians. The aim of the german-greek research project ECHO is to support the treatment of patients, who suffer from chronic obstructive pulmonary disease, a chronic respiratory disease. Usually the patients need to be examined by their physicians on a regular basis due to their chronic condition. Since this is very time consuming and expensive we developed an eHealth system which allows the physician to monitor patients condition remotely, e.g., via smart phones. This article is an extension of previous work, where we introduced a health data model and an associated platform-architecture for the management and analysis of the data provided by the patients. There we have also shown how the security of the data is ensured and we explained how the platform can be provided in a cloud-based environment using the OASIS standard TOSCA, which enables a self-contained management of cloud-services. In this article we provide a more detailed description about the health data analysis, provisioning and security aspects of the eHealth system.}, url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=ART-2016-18&engl=1} } @article {ART-2016-16, author = {Mathias Mormul and Pascal Hirmer and Matthias Wieland and Bernhard Mitschang}, title = {{Situation model as interface between situation recognition and situation-aware applications}}, journal = {Computer Science - Research and Development}, publisher = {Springer Berlin Heidelberg}, pages = {1--12}, type = {Article in Journal}, month = {November}, year = {2016}, doi = {10.1007/s00450-016-0335-2}, keywords = {Situation; Situation-awareness; Data management; Internet of things; Context; Context-awareness}, language = {English}, cr-category = {J.6 Computer-Aided Engineering, H.3.1 Content Analysis and Indexing}, ee = {http://link.springer.com/article/10.1007/s00450-016-0335-2}, contact = {pascal.hirmer@ipvs.uni-stuttgart.de}, department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems}, abstract = {The upcoming of internet of things draws interest of many companies and leads to the creation of smart environments. The foundation necessary for this purpose lies in the integration of sensors, which continuously provide context data of their environment. Based on this context, changes of state in the environment, i.e., situations, can be detected. However, with the huge amount of heterogeneous context and its processing, new challenges arise. Simultaneously, the dynamic behavior of the environment demands automated mechanisms for applications to adapt to the situations automatically and in a timely manner. To meet this challenge, we present (1) the situation model as a data model for integrating all data related to situation recognition, and (2) the management and provisioning of situations based on this situation model to further decouple situation recognition and applications adapting to recognized situations. Furthermore, we present a prototypical implementation of the situation model and its management.}, url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=ART-2016-16&engl=1} } @article {ART-2016-14, author = {Ana Cristina Franco da Silva and Pascal Hirmer and Matthias Wieland and Bernhard Mitschang}, title = {{SitRS XT – Towards Near Real Time Situation Recognition}}, journal = {Journal of Information and Data Management}, publisher = {-}, volume = {7}, number = {1}, pages = {4--17}, type = {Article in Journal}, month = {April}, year = {2016}, keywords = {Complex Event Processing; Internet of Things; Situation-awareness; Situation Recognition}, language = {English}, cr-category = {H.3 Information Storage and Retrieval, I.5 Pattern Recognition}, ee = {https://seer.lcc.ufmg.br/index.php/jidm/article/view/2109}, contact = {franco-da-silva@ipvs.uni-stuttgart.de}, department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems}, abstract = {Nowadays, the Internet of Things gains more and more attention through cheap, highly interconnected hardware devices that are attached with sensors and actuators. This results in an instrumented environment that provides sufficient context information to drive what is called situation recognition. Situations are derived from large amounts of context data, which is difficult to handle. In this article, we present SitRS XT, an extension of our previously introduced situation recognition service SitRS, to enable situation recognition in near real time. SitRS XT provides easy to use situation recognition based on Complex Event Processing, which is highly efficient. The architecture and method of SitRS XT is described and evaluated through a prototypical implementation.}, url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=ART-2016-14&engl=1} } @article {ART-2016-13, author = {Pascal Hirmer and Bernhard Mitschang}, title = {{TOSCA4Mashups: enhanced method for on-demand data mashup provisioning}}, journal = {Computer Science - Research and Development}, publisher = {Springer Berlin Heidelberg}, pages = {1--10}, type = {Article in Journal}, month = {October}, year = {2016}, doi = {10.1007/s00450-016-0330-7}, keywords = {Data Mashups; TOSCA; Provisioning; Cloud Computing}, language = {English}, cr-category = {E.0 Data General, E.1 Data Structures, H.1 Models and Principles}, ee = {http://link.springer.com/article/10.1007/s00450-016-0330-7}, contact = {Pascal.Hirmer@ipvs.uni-stuttgart.de}, department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems}, abstract = {Nowadays, the amount of data increases tremendously. Extracting information and generating knowledge from this data is a great challenge. To cope with this issue – oftentimes referred to as big data problem – we need effective means for efficient data integration, data processing, and data analysis. To enable flexible, explorative and ad-hoc data processing, several data mashup approaches and tools have been developed in the past. One of these tools is FlexMash – a data mashup tool developed at the University of Stuttgart. By offering domain-specific graphical modeling as well as a pattern-based execution, FlexMash enables usage by a wide range of users, both domain experts and technical experts. The core idea of FlexMash is a flexible execution of data mashups using different, user-requirement-dependent execution components. In this paper, we present a new approach for on-demand, automated provisioning of these components in a cloud computing environment using the Topology and Orchestration Specification for Cloud Applications. This enables many advantages for mashup execution such as scalability, availability and cost savings.}, url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=ART-2016-13&engl=1} } @article {ART-2016-12, author = {Pascal Hirmer and Matthias Wieland and Holger Schwarz and Bernhard Mitschang and Uwe Breitenb{\"u}cher and Santiago G{\'o}mez S{\'a}ez and Frank Leymann}, title = {{Situation recognition and handling based on executing situation templates and situation-aware workflows}}, journal = {Computing}, publisher = {Springer}, pages = {1--19}, type = {Article in Journal}, month = {October}, year = {2016}, doi = {10.1007/s00607-016-0522-9}, keywords = {Situation Recognition; IoT; Context; Integration; Cloud Computing; Workflows; Middleware}, language = {English}, cr-category = {J.6 Computer-Aided Engineering, H.3.1 Content Analysis and Indexing}, ee = {http://dx.doi.org/10.1007/s00607-016-0522-9}, contact = {pascal.hirmer@ipvs.uni-stuttgart.de}, department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems}, abstract = {Today, the Internet of Things has evolved due to an advanced interconnectivity of hardware devices equipped with sensors and actuators. Such connected environments are nowadays well-known as smart environments. Famous examples are smart homes, smart cities, and smart factories. Such environments should only be called {\ss}mart`` if they allow monitoring and self-organization. However, this is a great challenge: (1) sensors have to be bound and sensor data have to be efficiently provisioned to enable monitoring of these environments, (2) situations have to be detected based on sensor data, and (3) based on the recognized situations, a reaction has to be triggered to enable self-organization, e.g., through notification delivery or the execution of workflows. In this article, we introduce SitOPT---an approach for situation recognition based on raw sensor data and automated handling of occurring situations through notification delivery or execution of situation-aware workflows. This article is an extended version of the paper ''SitRS - Situation Recognition based on Modeling and Executing Situation Templates`` presented at the 9th Symposium and Summer School of Service-oriented Computing 2015.}, url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=ART-2016-12&engl=1} } @article {ART-2016-10, author = {Christoph Hochreiner and Stefan Schulte and Oliver Kopp}, title = {{Bericht zum 8. ZEUS Workshop}}, journal = {Softwaretechnik-Trends}, publisher = {Online}, volume = {36}, number = {2}, pages = {61--62}, type = {Article in Journal}, month = {August}, year = {2016}, issn = {0720-8928}, language = {German}, cr-category = {H.4.1 Office Automation}, ee = {http://pi.informatik.uni-siegen.de/gi/stt/36_2/03_Technische_Beitraege/ZEUS2016/bericht_zeus.pdf, http://pi.informatik.uni-siegen.de/gi/stt/36_2/index.html}, department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems}, abstract = {Es wird {\"u}ber den 8. ZEUS Workshop in Wien im Speziellen und dem ZEUS Workshop als Konzept im Allgemeinen berichtet.}, url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=ART-2016-10&engl=1} } @article {ART-2016-06, author = {Christoph Gr{\"o}ger and Christoph Stach and Bernhard Mitschang and Engelbert Westk{\"a}mper}, title = {{A mobile dashboard for analytics-based information provisioning on the shop floor}}, journal = {International Journal of Computer Integrated Manufacturing}, publisher = {Taylor \& Francis Inc.}, pages = {1--20}, type = {Article in Journal}, month = {May}, year = {2016}, doi = {10.1080/0951192X.2016.1187292}, keywords = {dashboard; cockpit; process optimisation; data analytics; business intelligence; data mining}, language = {English}, cr-category = {H.4.0 Information Systems Applications General, J.2 Physical Sciences and Engineering}, department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems}, abstract = {Today's turbulent global environment requires agility and flexibility of manufacturing companies to stay competitive. Thus, employees have to monitor their performance continuously and react quickly to turbulences which demands real-time information provisioning across all hierarchy levels. However, existing manufacturing IT systems, for example, manufacturing execution systems (MES), do hardly address information needs of individual employees on the shop floor. Besides, they do not exploit advanced analytics to generate novel insights for process optimisation. To address these issues, the operational process dashboard for manufacturing (OPDM) is presented, a mobile data-mining-based dashboard for workers and supervisors on the shop floor. It enables proactive optimisation by providing analytical information anywhere and anytime in the factory. In this paper, first, user groups and conceptual dashboard services are defined. Then, IT design issues of a mobile shop floor application on top of the advanced manufacturing analytics platform are investigated in order to realise the OPDM. This comprises the evaluation of different types of mobile devices, the development of an appropriate context model and the investigation of security issues. Finally, an evaluation in an automotive industry case is presented using a prototype in order to demonstrate the benefits of the OPDM for data-driven process improvement and agility in manufacturing.}, url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=ART-2016-06&engl=1} } @inbook {INBOOK-2016-04, author = {Uwe Breitenb{\"u}cher and Tobias Binz and Oliver Kopp and K{\'a}lm{\'a}n K{\'e}pes and Frank Leymann and Johannes Wettinger}, title = {{Hybrid TOSCA Provisioning Plans: Integrating Declarative and Imperative Cloud Application Provisioning Technologies}}, series = {Cloud Computing and Services Science}, publisher = {Springer International Publishing}, series = {Communications in Computer and Information Science}, volume = {581}, pages = {239--262}, type = {Article in Book}, month = {February}, year = {2016}, doi = {10.1007/978-3-319-29582-4_13}, isbn = {978-3-319-29581-7}, keywords = {Cloud application provisioning; TOSCA; Hybrid plans; Automation; Declarative modelling; Imperative modelling; Integration}, language = {English}, cr-category = {K.6 Management of Computing and Information Systems}, department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems; University of Stuttgart, Institute of Architecture of Application Systems}, abstract = {The efficient provisioning of complex applications is one of the most challenging issues in Cloud Computing. Therefore, various provisioning and configuration management technologies have been developed that can be categorized as follows: imperative approaches enable a precise specification of the low-level tasks to be executed whereas declarative approaches focus on describing the desired goals and constraints. Since complex applications employ a plethora of heterogeneous components that must be wired and configured, typically multiple of these technologies have to be integrated to automate the entire provisioning process. In a former work, we presented a workflow modelling concept that enables the seamless integration of imperative and declarative technologies. This paper is an extension of that work to integrate the modelling concept with the Cloud standard TOSCA. In particular, we show how Hybrid Provisioning Plans can be created that retrieve all required information about the desired provisioning directly from the corresponding TOSCA model. We validate the practical feasibility of the concept by extending the OpenTOSCA runtime environment and the workflow language BPEL.}, url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INBOOK-2016-04&engl=1} } @inbook {INBOOK-2016-01, author = {Pascal Hirmer and Bernhard Mitschang}, title = {{FlexMash - Flexible Data Mashups Based on Pattern-Based Model Transformation}}, series = {Rapid Mashup Development Tools}, publisher = {Springer International Publishing}, series = {Communications in Computer and Information Science}, volume = {591}, pages = {12--30}, type = {Article in Book}, month = {February}, year = {2016}, isbn = {978-3-319-28726-3}, doi = {10.1007/978-3-319-28727-0_2}, keywords = {ICWE rapid mashup challenge 2015; Data mashups; Transformation patterns; TOSCA; Cloud computing}, language = {English}, cr-category = {H.2.8 Database Applications, H.3.0 Information Storage and Retrieval General, E.1 Data Structures}, ee = {http://dx.doi.org/10.1007/978-3-319-28727-0_2}, department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems}, abstract = {Today, the ad-hoc processing and integration of data is an important issue due to fast growing IT systems and an increased connectivity of the corresponding data sources. The overall goal is deriving high-level information based on a huge amount of low-level data. However, an increasing amount of data leads to high complexity and many technical challenges. Especially non-IT expert users are overburdened with highly complex solutions such as Extract-Transform-Load processes. To tackle these issues, we need a means to abstract from technical details and provide a flexible execution of data processing and integration scenarios. In this paper, we present an approach for modeling and pattern-based execution of data mashups based on Mashup Plans, a domain-specific mashup model that has been introduced in previous work. This non-executable model can be mapped onto different executable ones depending on the use case scenario. The concepts introduced in this paper were presented during the Rapid Mashup Challenge at the International Conference on Web Engineering 2015. This paper presents our approach, the scenario that was implemented for this challenge, as well as the encountered issues during its preparation.}, url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INBOOK-2016-01&engl=1} }